Using an extended interval match to handle Slowly Changing Dimensions

Sometimes while developing the Data model for a Business Intelligence application, one comes across dimensional values that tend to change with time. Such dimensions are known as Slowly Changing Dimensions. For example, an employee joins a company at a Junior Executive level and stays at the same position for 1 year. After one year, the designation changes to Senior Executive and then changes to Project Manager after 3 years. The position field in this case will be treated as a Slowly Changing Dimension.

Such Slowly Changing Dimensions can be represented in Qlik Sense, provided the historical data is stored at the source with a proper "Position Start Date" and "Position End Date". ...

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